Computing devices are becoming ever smaller and full computing functionality can be found on phones and smart phones and other personal digital assistants (PDAs). As the computing devices become smaller, the various features of the computing devices may also become smaller. This includes a smaller input device for the user to enter input data into the computing device. One such input device is an optical navigation device. Many computing devices, large and small, are equipped with optical navigation devices, such as a mouse.
Finger mice are becoming more common on mobile phones, laptops, digital still cameras (DSC) and many other devices. In addition, 3D displays are becoming more popular. Current input or navigation devices (e.g. touch screens, mice, and finger mice including Optical Finger Navigation (OFN), Optical Navigation Mouse (ONM), Optical Joystick (OJ)) are typically two-dimensional (2D). Operating systems supporting 3D windows and operations requiring 3D control inputs are currently being developed. Even with a 2D display, a 3D navigation device is useful to recognize a wider range of gestures.
Most finger mice are modifications of a standard personal computer (PC) mouse, where a user moves their finger on top of a surface in X and Y directions. A sensor images the finger and uses the images to create X and Y motion vectors corresponding to the movement of the user's finger. These sensors are unable to detect movement in the Z axis. A common method to obtain depth information is to use two sensors which are spatially separated.
FIG. 1a shows an example of a finger mouse system with two image sensors. As can be seen in FIG. 1a, if the finger is moved vertically (i.e. along the Z axis) a feature on the sensors moves in the image plane. The same feature moves in opposite directions on the two sensors, permitting X and Y movement to be differentiated from Z movement. There may be some drawbacks to this approach, including: two sensors are required, which adds to the cost and space requirements of the device; at least two apertures are needed in the device, which may be considered to be unattractive; the images from the sensors are compared with one another, which may require additional processing; a high data rate may need to be supported by both the output transmitters of the sensors and also the receiver of the image processing unit; and accurately matching the two images, especially with a periodic structure such as a lateral shift, as found on a fingerprint, may be difficult and can produce incorrect triangulation or Z-height information.
Another approach to determining the distance is to measure the time it takes light to travel from the emitter, such as a light emitting diode (LED) or Vertical Cavity Surface Emitting Laser (VCSEL) to the object and then back to the sensor. A Single Photon Avalanche Detector (SPAD) is suitable for measuring this as it has a high electric field in the detector, which allows a photo-generated electron to be accelerated and quickly detected. In addition, the gain of the avalanche means that a digital pulse is produced and can be counted. However, a single SPAD may have no spatial resolution, and so a single detector may not determine if the object (i.e. finger) is moving, for example, along a circle with the SPAD at the center in the form of a common gesture. An approach to this drawback may comprise employing multiple SPAD devices, although the requirement for more apertures in the device housing may be unappealing. A possible system would employ 2 SPADs and 1 mouse sensor to extract motion in X, Y, and Z axes and may require 3 apertures.